Mapping multiple dimensions of forest diversity using spaceborne spectroscopy

J. Antonio Guzmán Q. , Jonathan A. Knott, Jesús Pinto-Ledezma, Philip Townsend, Jeannine Cavender-Bares 

Observing biodiversity across space and time is essential for advancing and verifying conservation efforts toward global biodiversity and sustainability goals. Spaceborne imaging spectroscopy has emerged as a revolutionary tool for quantifying and tracking forest diversity, yet its application at large spatial scales remains a central challenge. We develop a framework to map multiple dimensions of forest community composition and diversity by integrating imaging spectroscopy from two spaceborne sensors (DESIS and EMIT) with taxonomic, phylogenetic, and functional trait datasets, and 43,155 forest inventory plots across the Eastern United States. Our findings show that satellite-based spectral dissimilarity among forest communities is positively correlated with estimations of β-diversity from ground inventories. We further demonstrate that imaging spectroscopy can be used to predict ordination axes of β-diversity, enabling the mapping of multiple dimensions of forest community composition over large spatial extents. We showcase how these β-diversity ordinations and maps support the distribution modeling of 95 forest attributes and allow the evaluation of spatiotemporal changes in community composition. Our framework demonstrates that spaceborne imaging spectroscopy, when combined with inventory data, allows indirect yet comprehensive observation of forest diversity. This integrative approach sets the stage for scalable forest monitoring in support of global biodiversity conservation and forthcoming satellite missions.